Since a single biophysical technique is limited in the number of observable properties, one promising approach is the simultaneous consideration of data from multiple biophysical techniques. In the past, we have developed a data analysis program, SEDPHAT, for the global analysis of data from sedimentation velocity, sedimentation equilibrium, dynamic light scattering, isothermal titration calorimetry, surface binding, and different spectroscopies. These techniques produce data with widely different numbers of data points that have different susceptibility to systematic errors. Therefore, one key problem in their global modelling has been the question of how to weight different experiments relative to each other. We have further developed our analysis tools that address this problem. To this end, we have implemented Monte-Carlo statistical analysis functions, as well as procedures for the automated mapping of error surface projections in one or two dimensions. As a special case of this global modelling approach, we have also implemented in SEDPHAT models for the direct global fitting of multiple isothermal titration microcalorimetry isotherms acquired at different temperature, pH, and in buffers with different ionization enthalpies. Further, as the global analysis approach is being increasingly recognized as a highly useful tool in the isothermal titration microcalorimetry field, we have implemented more flexible tools for different calorimeter types and alternate injection strategies, and distributed this to the community in the SEDPHAT software.